An Inverse Neural Network approach is proposed to solve inverse problems in the field of material characterization in different electrical engineering applications. The flexibility and robustness of the inverse approach is demonstrated making reference to two different problems: the model identification of a magnetic material and the electric capacitance tomography of a polymeric material.

Materials characterization by Inverse Neural Network approach

Carcangiu, S.;Fanni, A.;Montisci, A.;
2016

Abstract

An Inverse Neural Network approach is proposed to solve inverse problems in the field of material characterization in different electrical engineering applications. The flexibility and robustness of the inverse approach is demonstrated making reference to two different problems: the model identification of a magnetic material and the electric capacitance tomography of a polymeric material.
9788887237306
Electric Capacitance Tomography; Inverse Models; Inverse problems; Material models parameter identification; Neural networks; Computer Networks and Communications; Hardware and Architecture; Energy Engineering and Power Technology; Renewable Energy, Sustainability and the Environment
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11584/234271
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